白话Elasticsearch14-深度探秘搜索技术之基于multi_match 使用most_fields策略进行cross-fields search弊端

文章目录

  • 概述
  • 官网
  • 示例

在这里插入图片描述

概述

继续跟中华石杉老师学习ES,第十四篇

课程地址: https://www.roncoo.com/view/55


官网

https://www.elastic.co/guide/en/elasticsearch/reference/7.2/query-dsl-multi-match-query.html

白话Elasticsearch14-深度探秘搜索技术之基于multi_match 使用most_fields策略进行cross-fields search弊端_第1张图片

白话Elasticsearch14-深度探秘搜索技术之基于multi_match 使用most_fields策略进行cross-fields search弊端_第2张图片

cross-fields搜索,一个唯一标识,跨了多个field。

比如一个人,标识,是姓名;一个建筑,它的标识是地址。

姓名可以散落在多个field中,比如first_name和last_name中,地址可以散落在country,province,city中。

跨多个field搜索一个标识,比如搜索一个人名,或者一个地址,就是cross-fields搜索

初步来说,如果要实现,可能用most_fields比较合适。因为best_fields是优先搜索单个field最匹配的结果,cross-fields本身就不是一个field的问题了。


示例

构造数据

POST /forum/article/_bulk
{ "update": { "_id": "1"} }
{ "doc" : {"author_first_name" : "Peter", "author_last_name" : "Smith"} }
{ "update": { "_id": "2"} }
{ "doc" : {"author_first_name" : "Smith", "author_last_name" : "Williams"} }
{ "update": { "_id": "3"} }
{ "doc" : {"author_first_name" : "Jack", "author_last_name" : "Ma"} }
{ "update": { "_id": "4"} }
{ "doc" : {"author_first_name" : "Robbin", "author_last_name" : "Li"} }
{ "update": { "_id": "5"} }
{ "doc" : {"author_first_name" : "Tonny", "author_last_name" : "Peter Smith"} }

执行查询

GET /forum/article/_search
{
  "query": {
    "multi_match": {
      "query": "Peter Smith",
      "type": "cross_fields",
      "fields": [
        "author_first_name",
        "author_last_name"
      ]
    }
  }
}


等同于 most_fileds


GET /forum/article/_search
{
  "query": {
    "multi_match": {
      "query": "Peter Smith",
      "type": "most_fields",
      "fields": [
        "author_first_name",
        "author_last_name"
      ]
    }
  }
}

返回结果

{
  "took": 2,
  "timed_out": false,
  "_shards": {
    "total": 1,
    "successful": 1,
    "skipped": 0,
    "failed": 0
  },
  "hits": {
    "total": 3,
    "max_score": 2.3258216,
    "hits": [
      {
        "_index": "forum",
        "_type": "article",
        "_id": "1",
        "_score": 2.3258216,
        "_source": {
          "articleID": "XHDK-A-1293-#fJ3",
          "userID": 1,
          "hidden": false,
          "postDate": "2017-01-01",
          "tag": [
            "java",
            "hadoop"
          ],
          "tag_cnt": 2,
          "view_cnt": 30,
          "title": "this is java and elasticsearch blog",
          "content": "i like to write best elasticsearch article",
          "sub_title": "learning more courses",
          "author_first_name": "Peter",
          "author_last_name": "Smith"
        }
      },
      {
        "_index": "forum",
        "_type": "article",
        "_id": "5",
        "_score": 1.7770995,
        "_source": {
          "articleID": "DHJK-B-1395-#Ky5",
          "userID": 3,
          "hidden": false,
          "postDate": "2019-05-01",
          "tag": [
            "elasticsearch"
          ],
          "tag_cnt": 1,
          "view_cnt": 10,
          "title": "this is spark blog",
          "content": "spark is best big data solution based on scala ,an programming language similar to java",
          "sub_title": "haha, hello world",
          "author_first_name": "Tonny",
          "author_last_name": "Peter Smith"
        }
      },
      {
        "_index": "forum",
        "_type": "article",
        "_id": "2",
        "_score": 0.5389965,
        "_source": {
          "articleID": "KDKE-B-9947-#kL5",
          "userID": 1,
          "hidden": false,
          "postDate": "2017-01-02",
          "tag": [
            "java"
          ],
          "tag_cnt": 1,
          "view_cnt": 50,
          "title": "this is java blog",
          "content": "i think java is the best programming language",
          "sub_title": "learned a lot of course",
          "author_first_name": "Smith",
          "author_last_name": "Williams"
        }
      }
    ]
  }
}

5.x版本中可能会出现: Peter Smith,匹配author_first_name,匹配到了Smith,这时候它的分数很高,为什么???
因为IDF分数高,IDF分数要高,那么这个匹配到的term(Smith),在所有doc中的出现频率要低,author_first_name field中,Smith就出现过1次
Peter Smith这个人,doc 1,Smith在author_last_name中,但是author_last_name出现了两次Smith,所以导致doc 1的IDF分数较低


cross-fields弊端

  • 问题1:只是找到尽可能多的field匹配的doc,而不是某个field完全匹配的doc
  • 问题2:most_fields,没办法用minimum_should_match去掉长尾数据,就是匹配的特别少的结果
  • 问题3:TF/IDF算法,比如Peter Smith和Smith Williams,搜索Peter Smith的时候,由于first_name中很少有Smith的,所以query在所有document中的频率很低,得到的分数很高,可能Smith Williams反而会排在Peter Smith前面

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